Aug 2026· Frontiers in Computing and Intelligent Systems· 0 citations· 18 references
TL;DR
The next big jump will not be driven by larger parameters, but smaller, more visible and dynamic systems that can be trusted by security analysts, as well as a disconnect between lab and reality.
Abstract
Web services are now pervasive in almost all industries, but this has made them a major target for hackers. Traditional signature-based solutions are no longer effective against zero‑day and polymorphic threats that evolve rapidly. The much heralded game‑changer is artificial intelligence (AI) particularly deep learning and more recently large language models. But the literature is fragmented: CNNs learn local features, Transformers capture long-range dependencies, and LLMs offer semantic understanding - yet each suffers from real-world limitations on interpretability, efficiency and security. In this survey we chart this progress and suggest that it's not model accuracy but trustworthiness that matters most. We carve up benchmark datasets (CSIC2010, CICIDS2017) and see a disconnect between lab and reality. Our message: the next big jump will not be driven by larger parameters, but smaller, more visible and dynamic systems that can be trusted by security analysts.
The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.
Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al.· IEEE Transactions on Softwar...· 178 citations· ⚡14
Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.
M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al.· e-Informatica Software Engin...· 157 citations· ⚡17
This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.
Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al.· Empirical Software Engineeri...· 127 citations· ⚡15
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al.· Journal of Systems and Softw...· 111 citations· ⚡8
This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6
The application of agile software methods and more recently the integration of Lean practices contribute to the trend of continuous improvement in the software industry. One such area warranting proper empirical evidence is a project’s operational efficiency when using the Kanban method. This short paper takes a new angle and explores waste in the Kanban-driven software development project context. A preliminary research model is presented for helping the consequent replication of the study. The results from the empirical analysis suggest Kanban can be an effective method in visualizing and organizing the current work, but does not prevent waste from creeping in, although the overall project outcome may be successful.
Marko Ikonen, Petri Kettunen, Nilay V. Oza et al.· EUROMICRO Conference on Soft...· 67 citations· ⚡9
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